The GLASOD project (1987-1990) has produced a world map of
human-induced soil degradation. Data were compiled in cooperation
with a large number of soil scientists throughout the world, using
uniform Guidelines and international correlation. The status of soil
degradation was mapped within loosely defined physiographic units
(polygons), based on expert judgement. The type, extent, degree,
rate and main causes of degradation have been printed on a global
map, at a scale of 1:10 million, and documented in a downloadable
database. Information about the areal extent of human-induced soil
degradation can be found in an explanatory note.

The GLASOD project (1987-1990) has produced a world map of
human-induced soil degradation. Data were compiled in cooperation
with a large number of soil scientists throughout the world, using
uniform Guidelines and international correlation. The status of soil
degradation was mapped within loosely defined physiographic units
(polygons), based on expert judgement. The type, extent, degree,
rate and main causes of degradation have been printed on a global
map, at a scale of 1:10 million, and documented in a downloadable
database. Information about the areal extent of human-induced soil
degradation can be found in an explanatory note.

The GLOBCOVER project was launched 2004 as an
initiative of ESA which is now evolving to an international
collaboration between ESA, FAO, UNEP, JRC, IGBP and GOFC-GOLD. The
objective of GLOBCOVER is to produce a global land-cover map for the
year 2005, using as main source of data the fine resolution (300 m)
mode data from MERIS sensor on-board
ENVISAT satellite,
acquired over the full year 2005. This new product intends to
complement and update other existing comparable global products,
such as the global land cover map for the year 2000 (GLC 2000) with
a resolution of 1 km produced by the JRC. Appropriate approaches for
the validation of the land cover products are planned to be defined
in consultation with CEOS.

GlobCover 2009 land cover map (1
product a year):

The land cover map is derived by an
automatic and regionally-tuned classification of a time series of
global MERIS FR mosaics for the year 2009. The global land cover map
counts 22 land cover classes defined with the United Nations (UN)
Land Cover Classification System (LCCS).

The GLOBCOVER project was launched 2004 as an
initiative of ESA which is now evolving to an international
collaboration between ESA, FAO, UNEP, JRC, IGBP and GOFC-GOLD. The
objective of GLOBCOVER is to produce a global land-cover map for the
year 2005, using as main source of data the fine resolution (300 m)
mode data from MERIS sensor on-board
ENVISAT satellite,
acquired over the full year 2005. This new product intends to
complement and update other existing comparable global products,
such as the global land cover map for the year 2000 (GLC 2000) with
a resolution of 1 km produced by the JRC. Appropriate approaches for
the validation of the land cover products are planned to be defined
in consultation with CEOS.

GlobCover 2009 land cover map (1
product a year):

The land cover map is derived by an
automatic and regionally-tuned classification of a time series of
global MERIS FR mosaics for the year 2009. The global land cover map
counts 22 land cover classes defined with the United Nations (UN)
Land Cover Classification System (LCCS).

This is the period during the year when both moisture
availability and temperature are conducive to crop growth. Thus, in
a formal sense, LGP refers to the number of days within
LGPwhen moisture
conditions are considered
adequate.

This is the period during the year when both moisture
availability and temperature are conducive to crop growth. Thus, in
a formal sense, LGP refers to the number of days within
LGPwhen moisture
conditions are considered
adequate.

The Global Subnational Prevalence of Child Malnutrition dataset
consists of estimates of the percentage of children with
weight-for-age z-scores that are more than two standard deviations
below the median of the NCHS/CDC/WHO International Reference
Population. Data are reported for the most recent year with
subnational information available at the time of development. The
data products include a shapefile (vector data) of percentage rates,
grids (raster data) of rates (per thousand in order to preserve
precision in integer format), the number of children under five (the
rate denominator), and the number of underweight children under five
(the rate numerator), and a tabular dataset of the same and
associated data. This dataset is produced by the Columbia University
Center for International Earth Science Information Network
(CIESIN).

The global data sets include two proxy poverty measurements: Infant Mortality Rates and Malnutrition (underweight children), all
translated to a common quarter-degree grid. A quarter-degree grid
cell is approximately 770 square kilometers (300 square miles) at
the equator, and progressively less at higher latitudes.

The Global Subnational Prevalence of Child Malnutrition dataset
consists of estimates of the percentage of children with
weight-for-age z-scores that are more than two standard deviations
below the median of the NCHS/CDC/WHO International Reference
Population. Data are reported for the most recent year with
subnational information available at the time of development. The
data products include a shapefile (vector data) of percentage rates,
grids (raster data) of rates (per thousand in order to preserve
precision in integer format), the number of children under five (the
rate denominator), and the number of underweight children under five
(the rate numerator), and a tabular dataset of the same and
associated data. This dataset is produced by the Columbia University
Center for International Earth Science Information Network
(CIESIN).

The global data sets include two proxy poverty measurements: Infant Mortality Rates and Malnutrition (underweight children), all
translated to a common quarter-degree grid. A quarter-degree grid
cell is approximately 770 square kilometers (300 square miles) at
the equator, and progressively less at higher latitudes.

The world is shrinking. Cheap flights, large scale commercial
shipping and expanding road networks, only 10% of the land area is remote – more
than 48 hours from a large city.This means that we are
better connected to everywhere else than ever before. But global
travel and international trade and just two of the forces that have
reshaped our world. A new map of Travel Time to Major Cities -
developed by the European Commission and the World Bank - captures
this connectivity and the concentration of economic activity and
also highlights that there is little wilderness left. The map shows
how accessible some parts of the world have become whilst other
regions have remained isolated. Accessibility - whether it is to
markets, schools, hospitals or water - is a precondition for the
satisfaction of almost any economic need. Furthermore, accessibility
is relevant at all levels, from local development to global trade
and this map fills an important gap in our understanding of the
spatial patterns of economic, physical and social
connectivity.

Accessibility maps are made for a specific purpose and they
cannot be used as a generic dataset to represent "the" accessibility
for a given study area. The data described and presented here were
used to create an urban/rural population gradient around large
cities of 50,000 or more people. The assumptions made in the
generation of this accessibility map can be found in the description and data sources links on the left. If these
assumptions sound reasonable for your requirements then the data are
available for download. If, however, the assumptions do
not match your requirements then you can use the information in
these pages as well as the software and external links to create your own
accessibility model.

This map was made for the World Bank's World Development Report
2009Reshaping Economic Geography. The message of
the report can be summarised as: Concentration
& density. 95% of the people live on just 10% of the
land "As economies grow from low to high income,
production becomes more concentrated spatially. Some places—cities,
coastal areas, and connected countries—are favored by producers.
The way to get both the immediate benefits of concentration of
production and the long-term benefits of a convergence in living
standards is economic integration." (WDR 2009, Overview). For
measuring the concentration of economic activity, instead of using
binary distinctions of rural versus urban, the report takes
advantage of global accessibility measures which can be combined
with data on population density to create a much finer typology
which is termed the Agglomeration Index (AI). The global map of
travel time to major cities (cities of 50,000 or more people in year
2000) is a useful dataset in its own right, but it is also a
component of the AI. This is described further in:

The world is shrinking. Cheap flights, large scale commercial
shipping and expanding road networks, only 10% of the land area is remote – more
than 48 hours from a large city.This means that we are
better connected to everywhere else than ever before. But global
travel and international trade and just two of the forces that have
reshaped our world. A new map of Travel Time to Major Cities -
developed by the European Commission and the World Bank - captures
this connectivity and the concentration of economic activity and
also highlights that there is little wilderness left. The map shows
how accessible some parts of the world have become whilst other
regions have remained isolated. Accessibility - whether it is to
markets, schools, hospitals or water - is a precondition for the
satisfaction of almost any economic need. Furthermore, accessibility
is relevant at all levels, from local development to global trade
and this map fills an important gap in our understanding of the
spatial patterns of economic, physical and social
connectivity.

Accessibility maps are made for a specific purpose and they
cannot be used as a generic dataset to represent "the" accessibility
for a given study area. The data described and presented here were
used to create an urban/rural population gradient around large
cities of 50,000 or more people. The assumptions made in the
generation of this accessibility map can be found in the description and data sources links on the left. If these
assumptions sound reasonable for your requirements then the data are
available for download. If, however, the assumptions do
not match your requirements then you can use the information in
these pages as well as the software and external links to create your own
accessibility model.

This map was made for the World Bank's World Development Report
2009Reshaping Economic Geography. The message of
the report can be summarised as: Concentration
& density. 95% of the people live on just 10% of the
land "As economies grow from low to high income,
production becomes more concentrated spatially. Some places—cities,
coastal areas, and connected countries—are favored by producers.
The way to get both the immediate benefits of concentration of
production and the long-term benefits of a convergence in living
standards is economic integration." (WDR 2009, Overview). For
measuring the concentration of economic activity, instead of using
binary distinctions of rural versus urban, the report takes
advantage of global accessibility measures which can be combined
with data on population density to create a much finer typology
which is termed the Agglomeration Index (AI). The global map of
travel time to major cities (cities of 50,000 or more people in year
2000) is a useful dataset in its own right, but it is also a
component of the AI. This is described further in: